Search: “models”

A PAC-Bayesian Analysis of Channel-Induced Degradation in Edge Inference

arXiv:2601.10915v2 Announce Type: replace-cross Abstract: In the emerging paradigm of edge learning, neural networks (NNs) are partitioned across distributed edge devices that collaboratively perform

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Hardware

A Semantic Autonomy Framework for VLM-Integrated Indoor Mobile Robots: Hybrid Deterministic Reasoning and Cross-Robot Adaptive Memory

DGX agent

arXiv:2605.02525v1 Announce Type: new Abstract: Autonomous indoor mobile robots can navigate reliably to metric coordinates using established frameworks such as ROS 2 Navigation 2, yet they lack the a

hardwarearxiv-cs-ro

5 May 2026

Ablation Study of Multimodal Perception, Language Grounding, and Control for Human-Robot Interaction in an Object Detection and Grasping Task

arXiv:2605.00963v1 Announce Type: new Abstract: This manuscript extends our previous multimodal human-robot interaction system by introducing a controlled ablation study of the three modules that most

researcharxiv-cs-ro

Adaptation of AI-accelerated CFD Simulations to the IPU platform

arXiv:2605.00462v1 Announce Type: cross Abstract: Intelligence Processing Units (IPU) have proven useful for many AI applications. In this paper, we evaluate them within the emerging field of AI for s

tutorialsarxiv-cs-ai

Adaptive Pluralistic Alignment: A pipeline for dynamic artificial democracy

arXiv:2605.01642v1 Announce Type: new Abstract: Prevailing alignment methods target a fixed set of preferences and therefore risk forcing value lock-in as societal norms evolve over time. We introduce

Adversarial Imitation Learning with General Function Approximation: Theoretical Analysis and Practical Algorithms

arXiv:2605.01778v1 Announce Type: new Abstract: Adversarial imitation learning (AIL), a prominent approach in imitation learning, has achieved significant practical success powered by neural network a

AFFormer: Adaptive Feature Fusion Transformer for V2X Cooperative Perception under Channel Impairments

arXiv:2605.01888v1 Announce Type: new Abstract: Accurate 3D object detection is essential for ensuring the safety of autonomous vehicles. Cooperative perception, which leverages vehicle-to-everything

An Adaptive Spatiotemporal Clustering Framework for 3D Ocean Subsurface Temperature Reconstruction

arXiv:2605.00860v1 Announce Type: cross Abstract: The reconstruction of ocean subsurface temperature (OST) using satellite remote sensing data holds significant scientific value for advancing the unde

Analyzing Adversarial Inputs in Deep Reinforcement Learning

arXiv:2402.05284v2 Announce Type: replace Abstract: In recent years, Deep Reinforcement Learning (DRL) has become a popular paradigm in machine learning due to its successful applications to real-worl

Automated In-the-Wild Data Collection for Continual AI Generated Image Detection

arXiv:2605.02567v1 Announce Type: new Abstract: The rapid advancement of generative Artificial Intelligence (AI) has introduced significant challenges for reliable AI-generated image detection. Existi

Barren Plateaus as Destructive Interference: A Diagnostic Framework and Implications for Structured Ansatzes

arXiv:2605.01319v1 Announce Type: cross Abstract: Barren plateaus (BPs) are usually described by the exponential suppression of gradient variance, but the mechanism by which gradient signal disappears

CNNs for Vis-NIR Chemometrics: From Contradiction to Conditional Design

arXiv:2605.02636v1 Announce Type: new Abstract: Near-infrared (NIR; a.k.a. NIRS) deep-learning studies in chemometrics increasingly report mutually inconsistent conclusions regarding convolutional neu

Coding agents are accelerating different types of software work to different degrees. When we architect teams, understanding these distincti…

Coding agents are accelerating different types of software work to different degrees. When we architect teams, understanding these distinctions helps us to have realistic expectations. Listing functio

tutorialsandrew-ng--x

Combining Facial Videos and Biosignals for Stress Estimation During Driving

arXiv:2601.04376v3 Announce Type: replace Abstract: Reliable stress recognition is critical in applications such as medical monitoring and safety-critical systems, including real-world driving. While

CycleRL: Sim-to-Real Deep Reinforcement Learning for Robust Autonomous Bicycle Control

arXiv:2603.15013v2 Announce Type: replace Abstract: Autonomous bicycles offer a promising agile solution for urban mobility and last-mile logistics. However, conventional control strategies often stru

safetyarxiv-cs-ro

Decouple and Cache: KV Cache Construction for Streaming Video Understanding

arXiv:2605.01858v1 Announce Type: new Abstract: Streaming video understanding requires processing unbounded video streams with limited memory and computation, posing two key challenges. First, continu

tutorialsarxiv-cs-cv

Deep Variational Inference Symbolic Regression

arXiv:2605.01067v1 Announce Type: new Abstract: Symbolic regression discovers explicit, interpretable equations without assuming a functional form in advance. A Bayesian approach strengthens this thro

Local Ai

Differentiable Kernel Ridge Regression for Deep Learning Pipelines

arXiv:2605.02313v1 Announce Type: new Abstract: Deep neural networks dominate modern machine learning, while alternative function approximators remain comparatively underexplored at scale. In this wor

local-aiarxiv-cs-lg

Dynamics Distillation for Efficient and Transferable Control Learning

arXiv:2605.01516v1 Announce Type: new Abstract: Robust control policy learning for autonomous driving requires training environments to be both physically realistic and computationally scalable, prope

safetyarxiv-cs-ro

Environment-Aware Indoor LoRaWAN Path Loss: Parametric Regression Comparisons, Shadow Fading, and Calibrated Fade Margins

arXiv:2510.04346v2 Announce Type: replace-cross Abstract: Indoor long range wide area network (LoRaWAN) propagation is shaped by structural and time-varying environmental factors, which limit single-s

Applications

Fine-Grained Graph Generation through Latent Mixture Scheduling

arXiv:2605.02780v1 Announce Type: cross Abstract: Structure aware graph generation aims to generate graphs that satisfy given topological properties. It has applications in domains such as drug discov

applicationsarxiv-cs-lg

From Cortical Synchronous Rhythm to Brain Inspired Learning Mechanism: An Oscillatory Spiking Neural Network with Time-Delayed Coordination

arXiv:2605.01656v1 Announce Type: cross Abstract: Human cognition emerges from coordinated spiking dynamics in distributed neural circuits, where information is encoded via both firing rates and preci

From Packets to Patterns: Interpreting Encrypted Network Traffic as Longitudinal Behavioral Signals

arXiv:2605.01616v1 Announce Type: new Abstract: Human behavior is difficult to observe continuously at scale, yet it leaves measurable traces in everyday device use. We test whether encrypted smartpho

From Spherical to Gaussian: A Comparative Analysis of Point Cloud Cropping Strategies in Large-Scale 3D Environments

arXiv:2605.02098v1 Announce Type: new Abstract: Large-scale 3D point clouds can consist of billions of points. Even after downsampling, these point clouds are too large for modern 3D neural networks.

From Static Constraints to Dynamic Adaptation: Sample-Level Constraint Release for Offline-to-Online Reinforcement Learning

arXiv:2511.03828v2 Announce Type: replace Abstract: Offline-to-online reinforcement learning (O2O RL) faces a central challenge between retaining offline conservatism and adapting to online feedback u

Agents

GA-VisAgent: A Multi-Agent application for code generation and visualization in interactive learning

arXiv:2605.01299v1 Announce Type: new Abstract: Geometric Algebra (GA) presents challenges to learners due to its highly abstract mathematical structure and complex operational rules, as translating a

agentsarxiv-cs-lg

Geometric and Spectral Alignment for Deep Neural Network II

arXiv:2605.02111v1 Announce Type: new Abstract: This paper develops the angular and static-channel component of Geometric and Spectral Alignment for residual Jacobian chains. Starting from Cartan-coor

Good in Bad (GiB): Sifting Through End-user Demonstrations for Learning a Better Policy

arXiv:2605.01529v1 Announce Type: new Abstract: Imitation learning offers a promising framework for enabling robots to acquire diverse skills from human users. However, most imitation learning algorit

safetyarxiv-cs-ro

Graph-Augmented Topological Internalization with Dual-Stream Classifiers for Medical Report Generation

arXiv:2605.02376v1 Announce Type: new Abstract: Automated medical report generation, MRG, holds substantial value for alleviating radiologist workload and enhancing diagnostic efficiency. However, mai

GRAVITY: Architecture-Agnostic Structured Anchoring for Long-Horizon Conversational Memory

arXiv:2605.01688v1 Announce Type: new Abstract: Long-horizon conversational agents rely on memory systems with increasingly sophisticated retrieval mechanisms. However, retrieved fragments are typical

researcharxiv-cs-cl

Hazard-Aware Traffic Scene Graph Generation

arXiv:2603.03584v2 Announce Type: replace Abstract: Maintaining situational awareness in complex driving scenarios is challenging. It requires continuously prioritizing attention among extensive scene

Heavy-Tailed Principal Component Analysis

arXiv:2603.11308v2 Announce Type: replace Abstract: Principal Component Analysis (PCA) is a cornerstone of dimensionality reduction, yet its classical formulation relies critically on second-order mom

High-Quality Spatial Reconstruction and Orthoimage Generation Using Efficient 2D Gaussian Splatting

arXiv:2503.19703v3 Announce Type: replace Abstract: Highly accurate geometric precision and dense image features characterize True Digital Orthophoto Maps (TDOMs), which are in great demand for applic

How Good is Your Wikipedia? Auditing Data Quality for Low-resource and Multilingual NLP

arXiv:2411.05527v3 Announce Type: replace Abstract: Wikipedia's perceived high quality and broad language coverage have established it as a fundamental resource in NLP. However, in recent years, such

researcharxiv-cs-cl

Applications

Human Activity Recognition Method for Moderate Violence Detection

arXiv:2605.02659v1 Announce Type: new Abstract: Physical violence in public spaces is a significant public health concern, with minor incidents such as pushing often serving as precursors to more seve

applicationsarxiv-cs-cv

Hyp2Former: Hierarchy-Aware Hyperbolic Embeddings for Open-Set Panoptic Segmentation

arXiv:2605.02580v1 Announce Type: new Abstract: Recognizing unknown objects is crucial for safety-critical applications such as autonomous driving and robotics. Open-Set Panoptic Segmentation (OPS) ai

IMPACT-Scribe: Interactive Temporal Action Segmentation with Boundary Scribbles and Query Planning

arXiv:2605.01668v1 Announce Type: new Abstract: Dense temporal annotation of procedural activity videos is vital for action understanding and embodied intelligence but remains labor-intensive due to r

Industry

in particular, the combination of improvements to speed, intelligence, personality, and great memory/personalization feels like a more-than-…

in particular, the combination of improvements to speed, intelligence, personality, and great memory/personalization feels like a more-than-sum-of-the-parts thing when it all hits together the new ins

industrysam-altman--x

Investigating Anthropometric Fidelity in SAM 3D Body

arXiv:2601.06035v2 Announce Type: replace-cross Abstract: The release of SAM 3D Body is a recent development in human mesh recovery, demonstrating improved performance in producing clean, topologicall

KANs need curvature: penalties for compositional smoothness

arXiv:2605.02190v1 Announce Type: new Abstract: Kolmogorov-Arnold networks (KANs) offer a potent combination of accuracy and interpretability, thanks to their compositions of learnable univariate acti

Hardware

LEAP: Layer-wise Exit-Aware Pretraining for Efficient Transformer Inference

arXiv:2605.01058v1 Announce Type: cross Abstract: Layer-aligned distillation and convergence-based early exit represent two predominant computational efficiency paradigms for transformer inference; ye

hardwarearxiv-cs-cl

Learning to Place Objects with Programs and Iterative Self Training

arXiv:2503.04496v2 Announce Type: replace-cross Abstract: In this work we study indoor scene object placement. Given a 3D indoor scene and an object, the task is to predict placement locations within

Agents

LIE: LiDAR-only HD Map Construction with Intensity Enhancement via Online Knowledge Distillation

arXiv:2605.01478v1 Announce Type: new Abstract: Online High-Definition (HD) map construction is a key component of autonomous driving. Recent methods rely on multi-view camera images for cost-effectiv

agentsarxiv-cs-cv

Limited-Angle Tomography Reconstruction via Projector Guided 3D Diffusion

arXiv:2510.06516v2 Announce Type: replace Abstract: Limited-angle electron tomography aims to reconstruct 3D shapes from 2D projections of Transmission Electron Microscopy (TEM) within a restricted ra

tutorialsarxiv-cs-cv

Local Ai

Linearizing Vision Transformer with Test-Time Training

arXiv:2605.02772v1 Announce Type: new Abstract: While linear-complexity attention mechanisms offer a promising alternative to Softmax attention for overcoming the quadratic bottleneck, training such m

local-aiarxiv-cs-cv

Agents

LinkAnchor: An Autonomous LLM-Based Agent for Issue-to-Commit Link Recovery

arXiv:2508.12232v3 Announce Type: replace-cross Abstract: Issue-to-commit link recovery in software repositories is fundamental to software traceability and project management, yet it remains a challe

agentsarxiv-cs-ai

Linking spatial biology and clinical histology via Haiku

arXiv:2605.00925v1 Announce Type: cross Abstract: Integrating molecular, morphological, and clinical data is essential for basic and translational biomedical research, yet systematic frameworks for jo

LLM-Based Agentic Negotiation for 6G: Addressing Uncertainty Neglect and Tail-Event Risk

arXiv:2511.19175v2 Announce Type: replace-cross Abstract: A critical barrier to the trustworthiness of sixth-generation (6G) agentic autonomous networks is the uncertainty neglect bias; a cognitive te

safetyarxiv-cs-ai